Atmos. Chem. Phys., 14, 7769–7779, 2014
www.atmos-chem-phys.net/14/7769/2014/
doi:10.5194/acp-14-7769-2014
© Author(s) 2014. CC Attribution 3.0 License.
Sensitivity of simulated climate to latitudinal distribution of solar
insolation reduction in solar radiation management
A. Modak and G. Bala
Divecha Centre for Climate Change & Centre for Atmospheric and Oceanic Sciences, Indian Institute of Science, Bangalore,
560 012, India
Correspondence to: A. Modak (amatcaos@caos.iisc.ernet.in)
Received: 15 July 2013 – Published in Atmos. Chem. Phys. Discuss.: 1 October 2013
Revised: 13 June 2014 – Accepted: 23 June 2014 – Published: 5 August 2014
Abstract. Solar radiation management (SRM) geoengineering has been proposed as a potential option to counteract
climate change. We perform a set of idealized geoengineering simulations using Community Atmosphere Model version 3.1 developed at the National Center for Atmospheric
Research to investigate the global hydrological implications
of varying the latitudinal distribution of solar insolation reduction in SRM methods. To reduce the solar insolation we
have prescribed sulfate aerosols in the stratosphere. The radiative forcing in the geoengineering simulations is the net
forcing from a doubling of CO2 and the prescribed stratospheric aerosols. We find that for a fixed total mass of sulfate aerosols (12.6 Mt of SO4 ), relative to a uniform distribution which nearly offsets changes in global mean temperature from a doubling of CO2 , global mean radiative forcing is
larger when aerosol concentration is maximum at the poles
leading to a warmer global mean climate and consequently
an intensified hydrological cycle. Opposite changes are simulated when aerosol concentration is maximized in the tropics. We obtain a range of 1 K in global mean temperature
and 3 % in precipitation changes by varying the distribution
pattern in our simulations: this range is about 50 % of the
climate change from a doubling of CO2 . Hence, our study
demonstrates that a range of global mean climate states, determined by the global mean radiative forcing, are possible
for a fixed total amount of aerosols but with differing latitudinal distribution. However, it is important to note that this is
an idealized study and thus not all important realistic climate
processes are modeled.
1
Introduction
Atmospheric concentrations of the greenhouse gases (GHGs)
such as carbon dioxide (CO2 ), methane (CH4 ) and nitrous
oxide (N2 O) have been increasing since pre-industrial periods primarily because of fossil fuel use and land-use change
(IPCC, 2007). Their increase has the potential to cause long
term climate change by altering the planetary radiation budget. To moderate future climate change and its impacts, several geoengineering proposals have been made recently. By
definition, geoengineering is an intentional large-scale manipulation of the environment, particularly intended to counteract the undesired consequences of anthropogenic climate
change (Keith, 2000).
Proposed geoengineering methods are classified into two
main groups: solar radiation management (SRM) methods
and carbon dioxide removal (CDR) methods (Shepherd et al.,
2009). In the first approach, the amount of solar absorption
by the planet is reduced by artificially enhancing the planetary albedo so that the reduced insolation compensates the
radiative forcing due to rising GHGs. Some proposed methods are injecting sulfate aerosols in the stratosphere (Budkyo,
1982; Crutzen, 2006; Wigley, 2006) and placing space-based
sun shields in between the Sun and the Earth (Early, 1989).
Other SRM methods include marine cloud brightening and
enhancement of land/ocean surface albedo. CDR methods
propose to accelerate the removal of CO2 from the atmosphere and thus they deal with the root cause of global warming (Shepherd et al., 2009).
Past climate modeling studies have modeled the effects
of space-based SRM methods by reducing the solar constant (Govindasamy and Caldeira, 2000; Matthews and
Caldeira, 2007; Caldeira and Wood, 2008; Lunt et al., 2008)
Published by Copernicus Publications on behalf of the European Geosciences Union.
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A. Modak and G. Bala: Sensitivity of climate to latitudinal distribution of solar reduction
or modeled the effects of stratospheric aerosol methods
(Robock et al., 2008; Rasch et al., 2008a; Rasch et al., 2008b;
Heckendorn et al., 2009; Jones et al., 2010). It has been
shown (e.g., Bala et al., 2008) that SRM geoengineering
would lead to a weakening of the global water cycle when
the global mean temperature change is offset exactly. A recent study (Tilmes et al., 2013) using 12 models from the
Geoengineering Model Intercomparison Project (GeoMIP)
confirms this weakening of the hydrological cycle under a
multi-model framework. Further, it has been shown (Robock
et al., 2008; Ricke et al., 2010; Tilmes et al., 2013) that the
level of compensation will vary with residual changes larger
in some regions than others. Therefore, some recent studies
(Ban-Weiss and Caldeira, 2010; MacMartin et al., 2012) determine an optimal reduction in solar radiation in both space
and time so that the geoengineered world is more similar to
the control climate while other studies (Irvine et al., 2010;
Ricke et al., 2010) analyze the effect of different levels of
uniform SRM forcing on regional climate response. BanWeiss and Caldeira (2010) vary both the amount and the latitudinal distribution of aerosols to offset either the zonally
averaged changes in surface temperature or the water budget. However, a simple and clear understanding of the effects of systematically varying the latitudinal distribution of
aerosols and hence solar insolation reduction (e.g., more concentration in the tropics or high latitudes) on the hydrological cycle and surface temperature is lacking. In this study,
we perform multiple idealized SRM geoengineering simulations with constant total amount of sulfate aerosols but with
systematically varying the latitudinal distribution.
We caution that our simulations are highly idealized and
they are not meant to represent realistic latitudinal distribution of aerosols in geoengineering scenarios and may not be
technologically achievable. Rather, they are designed to elucidate the fundamental properties of the climate system when
the latitudinal distribution of aerosols and hence solar insolation reduction is systematically altered. We believe that our
study should be considered as complementary to a previous
work (Ban-Weiss and Caldeira, 2010), because not only we
vary the latitudinal distribution of aerosols but we also provide a constraint by fixing the total amount of aerosols which
facilitates a clear insight on the effects of varying the latitudinal distribution of aerosols.
2
Model and experiments
We used the atmospheric general circulation model, CAM3.1
(Community Atmosphere Model version 3.1) developed at
the National Center for Atmospheric Research (NCAR)
(Collins et al., 2004). It is coupled to the land model CLM3.0
(Community Land Model version 3.0) and to a slab ocean
model (SOM) with a thermodynamic sea ice model to represent the interactions with the ocean and sea ice components
of the climate system. The model can be also configured with
Atmos. Chem. Phys., 14, 7769–7779, 2014
prescribed sea surface temperature and sea ice fraction. The
horizontal resolution is 2◦ latitude and 2.5◦ longitude and the
model has 26 vertical levels and the top of the model (TOM)
is at 3 hPa.
We performed two sets of simulations: (1) fixed-SST (sea
surface temperature) simulations to estimate the radiative
forcing which is measured as the net radiative flux change
at the top of the atmosphere (Hansen et al., 1997). This
method allows the rapid adjustment of the atmosphere and
land components before radiative forcing is evaluated. (2)
The other set includes the SOM simulations to study the climate change. For both sets of simulations, fixed-SST and
SOM, we performed 12 cases: a control (1 × CO2 ), doubled CO2 climate (2 × CO2 ) and ten geoengineering simulations each with differing latitudinal distribution of sulfate
aerosol concentrations but with fixed total amount. The concentration of atmospheric CO2 in 1 × CO2 is 390 ppm and
is 780 ppm in 2 × CO2 and geoengineering simulations. The
concentrations of other greenhouse gases are kept constant
in all simulations. The background sulfate aerosol amount in
this version of the model is 1.38 Mt SO4 . The fixed-SST simulations lasted for 30 years and the last 20 years are used to
calculate the radiative forcing. The SOM simulations lasted
for 60 years and the last 30 years are used for climate change
analysis since all SOM simulations reach a near-equilibrium
climate state in approximately 25 years.
As in Ban-Weiss and Caldeira (2010), the additional sulfate aerosols are prescribed in the geoengineering cases (Table 1, Fig. 1a) and hence it is not transported around. However, in contrast to Ban-Weiss and Caldeira (2010), we introduce the constraint that the total amount of aerosol is constant (12.6 Mt SO4 ) while latitudinal distributions are varied.
Since aerosols are prescribed at TOM, the effect is essentially equivalent to making latitudinal changes to the solar
constant. Sulfate aerosol particle size is prescribed and is assumed to be log-normally distributed with dry median radius
≈ 0.05 µm and geometric standard deviation ≈ 2.0 (as used
in the “small particle” geoengineering scenario in a previous study (Rasch et al., 2008b)). The indirect aerosol effects
are not modeled and aerosol loadings for other species like
sea-salt, soil dust, black and organic carbon are unchanged in
each of the simulations.
Besides a simulation with uniform aerosol concentration,
our geoengineering simulations can be grouped into two
categories: (1) Three Tropics simulations with maximum
aerosol concentrations at the equator and (2) six Polar cases
with maximum concentrations at the poles. The latitudinal
distribution of the stratospheric sulfate aerosol concentration
are developed using the expression:
Q(ϕ) = a + b cos(ϕ),
(1)
where Q is the concentration of the additional mass of sulfate aerosols, a and bcos(ϕ) are the uniform and non-uniform
components of the distributions and ϕ represents the latitude.
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A. Modak and G. Bala: Sensitivity of climate to latitudinal distribution of solar reduction
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Table 1. Description of different geoengineering experiments. Total additional mass is 12.6 Mt SO4 in all the geoengineering simulations but
the distribution varies.
Name of the
experiments
Uniform
Polar1
Polar2
Polar3
Polar4
Polar5
Polar6
Tropics1
Tropics2
Tropics3
a (mg m−2 )
b (mg m−2 )
Total mass from
uniform component (Mt)
Total mass from
non-uniform component (Mt)
Total mass
(Mt)
24.70
23.52
21.56
19.60
17.64
15.68
13.72
26.66
28.62
30.58
−
3.19
8.55
13.89
19.22
24.56
29.90
−5.34
−10.67
−16.02
12.60
12.00
11.00
10.00
9.00
8.00
7.00
13.60
14.60
15.60
−
0.60
1.60
2.60
3.60
4.60
5.60
−1.00
−2.00
−3.00
12.60
12.60
12.60
12.60
12.60
12.60
12.60
12.60
12.60
12.60
Figure 1. (a) Latitudinal profiles of sulfate aerosol concentration in the SRM geoengineering experiments. Polar1–6 have maximum concentration over the poles and Tropics1–3 have maximum at the equator. (b) Surface temperature change (K) vs precipitation change (%) relative
to the 1 × CO2 case from slab ocean simulations (global mean values – squares, land mean values – stars, ocean mean values – triangles).
There is warming in all Polar cases relative to the Uniform case and a concomitant increase in precipitation. Opposite is the case for Tropics
cases. None of the regression lines pass through origin; temperature and precipitation cannot be offset simultaneously. In the case of land and
ocean, 1TS and 1P represent the averages over the respective domain. (c) Radiative forcing (RF) vs surface temperature change. Polar cases
have larger forcing relative to the Uniform case and hence are warmer while opposite is true for Tropics cases. (d) Radiative forcing vs %
precipitation change. Precipitation increases with residual RF (i.e. with increase in polar weighting) while decreases with increase in tropical
weighting. In (b), (c) and (d), the horizontal and vertical bars represent the standard error of the respective variables which are calculated
from the last 30 years of 60-year SOM simulations, while in the case of radiative forcing it is calculated from the last 20 years of 30-year
fixed-SST simulations.
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A. Modak and G. Bala: Sensitivity of climate to latitudinal distribution of solar reduction
Both a and b are varied to obtain various distributions of concentrations (Table 1, Fig. 1a). However, when Q is integrated
over the sphere, the result is 12.6 Mt in all cases. Our choice
of 12.6 Mt for Q is dictated by the uniform distribution case
which had near-zero global mean temperature change relative to the control case. In each of the geoengineering simulations aerosol mass is added to the model background concentration at the TOM as was done in a recent study (BanWeiss and Caldeira, 2010). An experiment where the same
total mass (12.6 Mt) of aerosol is distributed uniformly over
the globe between 61 hPa to 9.8 hPa (15–30 km) with a maximum at 30 hPa (22 km) showed that the radiative forcing is
nearly the same as in our uniform distribution geoengineering case and hence the main conclusions reached in this study
are unlikely to be altered by distributing the aerosols within
the stratosphere.
3
3.1
Results
Global mean temperature and precipitation
response
Unless otherwise specified the changes discussed here are
with respect to the 1 × CO2 case. We find that the radiative
forcing for doubling the atmospheric CO2 (2 × CO2 ) to be
3.5 W m−2 while the global mean surface temperature rise
is about 2.1 K and the precipitation increase is about 4.3 %
(i.e. ≈ 2 % K−1 ) in agreement with the previous studies using the same model (Rasch et al., 2008b; Bala et al., 2009).
The slopes in Fig. 1c and d indicate a climate sensitivity of
0.53 K per Wm−2 and precipitation sensitivity (% change in
precipitation for unit change in radiative forcing) of 1.5 %
per Wm−2 respectively, values that are similar to Bala et
al. (2009).
The slight warming in the geoengineering case where forcing is close to zero (the case Polar1 in Fig. 1c) is because
of the CO2 physiological forcing (Betts et al., 2007; Cao et
al., 2010) which is not counteracted by a decrease in solar
flux. CO2 -physiological forcing refers to the direct physiological response of plants to elevated CO2 : the plant stomata
open less widely and thus decrease the canopy transpiration
which in turn reduces evapotranspiration and causes surface
warming. Therefore, in the zero radiative forcing case (Polar1) where CO2 radiative forcing is countered by the reduction in solar radiation, the CO2 -physiological forcing could
lead to a slight warming. It is also likely that the slight non
uniform distribution of aerosols in Polar1 case could partly
contribute to this warming.
In agreement with past studies (e.g., Lunt et al., 2008; Bala
et al., 2008; Tilmes et al. 2013), we find that in the geoengineering scenario with uniform distribution of aerosol there
is a decline in precipitation though there is a near cancellation of surface temperature change (Fig. 1b). This occurs
because of the differing fast response (changes that occur
Atmos. Chem. Phys., 14, 7769–7779, 2014
before global mean surface temperature change) in precipitation for solar and CO2 -forcing (Allen and Ingram, 2002;
Bala et al., 2008, 2009; Andrews et al., 2009): long-wave
absorption by CO2 in the atmosphere can contribute to increased vertical stability and suppress precipitation but this
fast response mechanism is nearly absent for solar forcing
because the atmosphere is nearly transparent to solar radiation. However, since the slow response (changes that are
associated with global mean surface temperature change) is
same for CO2 and solar forcings (Bala et al. 2010), the total
changes in rainfall are larger to solar forcing than to equivalent CO2 forcing. Because of this differing hydrological sensitivity to solar and CO2 forcing, insolation reductions (in
geoengineering scenarios) sufficient to offset the entirety of
global-scale temperature increases would lead to a decrease
in global mean precipitation. This suppression of precipitation is simulated in all geoengineering simulations (the regression line does not pass through the origin in Fig. 1b).
Our geoengineering simulations with varying aerosol distributions indicate a linear relationship between the global
mean surface temperature change and the precipitation
change (Fig. 1b). The regression lines do not pass through
the origin which implies that none of the distribution can
offset global mean temperature and precipitation simultaneously. Though the total amount of aerosols in each of the
geoengineering simulation is fixed, we obtain a range of 1 K
(residual cooling of 0.3 K for the Tropics3 case to residual
warming of 0.7 K for the Polar6 case) in global mean temperature and 3 % (residual drying of 2 % for Tropics3 case to
residual increase of 1 % for the Polar6 case) in precipitation
changes which are about 50 % or more of the changes that
result from doubling of CO2 . This indicates that a range of
climate states are possible for a constant amount of aerosols.
As the polar maximum of the aerosol concentration increases the global mean temperature increases with concomitant increase in global mean precipitation as implied
by the linear relationship in Fig. 1b. One of the polar maximum SRM simulations (Polar3) almost offsets the changes
in global mean precipitation but it has a residual warming of 0.4 ◦ C. Our results are broadly in agreement with
other modeling studies: in an Arctic geoengineering study
(Caldeira and Wood, 2008) with reduced solar constant only
over arctic, residual global mean warming and enhancements
of global precipitation are found.
In contrast, as the magnitude of the tropical maximum
concentration increases both global mean temperature and
precipitation decreases. One of the Tropics cases (Tropics1)
where the temperature change is nearly zero shows a reduction in the global mean precipitation. Our Tropics simulations can be qualitatively compared to the Mount Pinatubo
(15◦ N) eruption in 1991 because the distribution of aerosols
in Tropics simulations has reasonable resemblance to the distribution of aerosols after a few weeks of the eruption (the
volcanic aerosols occupied a latitude band of 20◦ S to 30◦ N;
McCormick et al., 1995). Further, similarly to the global
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A. Modak and G. Bala: Sensitivity of climate to latitudinal distribution of solar reduction
Figure 2. Change in planetary albedo in fixed-SST vs surface temperature change in slab ocean geoengineering simulations. The radiative forcing associated with albedo changes drive the temperature changes. Polar cases have lower albedo changes relative to the
Uniform case and hence are warmer and wetter while opposite is
true for Tropics cases. The horizontal and vertical bars represent
the standard error of the respective variables; temperature standard
errors are calculated from the last 30 years of 60-year SOM simulations while albedo standard errors are calculated from the last
20 years of 30-year fixed-SST simulations.
mean precipitation and temperature decline after the eruption
(Parker et al. 1996; Trenberth and Dai, 2007), we also simulate a reduction of global mean temperature and precipitation
in our Tropics simulations (except in Tropics1 case). Interestingly, we find that in none of the geoengineering scenarios
considered in this study, changes in global mean surface temperature and precipitation can be offset simultaneously over
either land or ocean. We also notice that the hydrological sensitivity (% change in precipitation per unit change in temperature) is almost same over both land and ocean (Fig. 1b).
Here, we have defined the hydrological sensitivity over land
(ocean) as the ratio of change in land (ocean) averaged precipitation to change in land (ocean) averaged surface temperature.
We find that the prescribed aerosols with different latitudinal distributions along with doubled CO2 concentrations
(geoengineering simulations) lead to different global mean
forcings (Fig. 1c and d). Since there are linear relationships
between the radiative forcing and the changes in global mean
temperature (Fig. 1c) and between the temperature and precipitation changes (Fig. 1b), we find a linear relationship
between the radiative forcing and the precipitation changes
(Fig. 1d). The Polar geoengineering scenarios have positive
residual radiative forcing while the Tropics scenarios have
negative residual radiative forcing because the solar forcing
is less effective over the poles relative to the tropics (Fig. 1c).
This is further confirmed in Fig. 2 which shows that the Polar
cases have smaller increase in the planetary albedo compared
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to the Tropics cases. The radiative forcing associated with
planetary albedo changes drive the temperature changes. The
Polar cases have lower albedo changes relative to the Uniform case and hence are warmer and wetter while opposite
is true for Tropics cases. The variation of global mean surface temperature and precipitation with global mean radiative
forcing (Fig. 1c and d) shows that as the maximum aerosol
concentration over the poles increases (Polar1 to Polar6) the
residual forcing increases and hence the global mean temperature and precipitation increase. Similarly, as the maximum aerosol concentration over the equator increases (Tropics1 to Tropics3), an opposite variation is noticed. In order
to confirm that the global mean radiative forcing is sufficient to infer the global mean climate change we performed
four additional geoengineering simulations with total amount
of aerosols varied (10, 11, 13, and 14 Mt) for the Uniform
distribution case. We find that the global mean temperature
and precipitation changes follow the changes in global mean
forcing (Fig. 3) for this set of simulations too.
To further investigate the degree of departure of the different geoengineering simulations from the control, we calculate the root mean square difference between the spatial patterns in geoengineered climates and the control climate and
normalize this root mean square difference by the standard
deviation of the control scenario (NRMSD). A value less
than 1 for NRMSD would suggest that the geoengineered
climate is indistinguishable from the control climate. Further, the geoengineering simulation with the smallest value
for this quantity is the one that is closest to the control. In
our study, we find that the NRMSD for temperature increases
as the maximum concentration of aerosols at the poles increases and the NRMSD for precipitation increases as tropical maximum is increased (Fig. 4). When all grid points in
the latitude-longitude domain are considered for computing
the NRMSD (Fig. 4a), it shows large variations: 0.40 to 1.4
for surface temperature and 0.25 to 0.40 for precipitation.
In the case of NRMSD calculated for zonal-mean profile
(Fig. 4b), the spread is relatively less: 0.30 to 0.95 for surface temperature and 0.27 to 0.38 for precipitation. If the objective is to minimize the NRMSD in both temperature and
precipitation simultaneously relative to the control case, the
Uniform case is closest to the control case since it has the
least distance from the origin in Fig. 4. Since the NRMSD
for both temperature and precipitation are less than 2 standard deviations for all the geoengineering cases (Fig. 4), we
conclude that these simulations are not significantly (95 %
confidence level) different from the control.
3.2
Spatial pattern of temperature and precipitation
responses
The change in zonal-mean surface temperature between
the geoengineering cases and the control case (1 × CO2 )
show, similar to changes in global annual mean values, a
monotonic increase at each latitude with increased polar
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A. Modak and G. Bala: Sensitivity of climate to latitudinal distribution of solar reduction
Figure 3. (a) Radiative forcing (RF) vs surface temperature change,
(b) radiative forcing vs % precipitation change for uniform distribution scenarios with 10 Mt, 11 Mt, 12.6 Mt, 13 Mt and 14 Mt. More
aerosol mass leads to negative residual radiative forcing and hence
cooler and drier climate, and smaller aerosol mass leads to positive
residual radiative forcing and hence warmer and wetter climate. In
(a) and (b) the horizontal and vertical bars represent the standard
error of the respective variables. Results shown are averages of the
last 20 years of 50-year SOM simulations for temperature and precipitation while the last 20 years of 40-year fixed-SST simulations
are used for radiative forcing calculations.
weighting (Fig. 5a). We notice a similar monotonic increase
in zonal-mean land and zonal-mean ocean surface temperature (Fig. 6a and b). Further, we find that almost all geoengineering simulation show residual high latitude warming.
In the Tropics cases, we find smaller residual warming in
the high latitudes and cooler tropics. Similar to temperature
changes, the change in zonal-mean precipitation between the
geoengineering cases and the control case show a monotonic increase at each latitudes with increased polar weighting (Fig. 5b, 6c and d). We find large changes in precipitation
Atmos. Chem. Phys., 14, 7769–7779, 2014
Figure 4. Normalized root mean square difference (NRMSD) of
surface temperature and precipitation between geoengineering and
control simulation normalized by respective standard deviations
computed for the global domain (top panel) and for the zonal averages (bottom panel). The annual means of the last 30 years of the
60-year control simulation are used to estimate the standard deviation. Simulation nearest to x-axis represents the best precipitation
mitigating scenario while the one closest to y-axis represents the
best surface temperature mitigating scenario. Scenarios with maximum aerosol concentrations at the poles have larger NRMSD in
temperature and conversely simulations with maximum at the equator have larger NRMSD in precipitation.
in the tropics which is likely to be seen as shifts in the intertropical convergence zone (ITCZ) but closer examination
(Fig. 7) shows that the position of ITCZ remains the same in
all the cases and the monotonic increase in precipitation with
poleward weighting is clearly seen. Sharp gradients in precipitation response around the equator (region of ITCZ) are
simulated in all our simulations. The sharp gradient in zonal
mean precipitation response we simulate in the 2 × CO2 case
in the tropics is similar to the near-term CMIP5 multi-model
projections (Fig. 11.13a in IPCC, 2013). The precipitation
response simulated over the high latitudes in 2 × CO2 case
is also in agreement with the CMIP5 multi-model projections. In the case of the Tropics geoengineering simulations
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Figure 6. Changes in zonal mean surface temperature (1TS), precipitation (1P) and precipitation minus evaporation (1PmE) over
ocean (left panels) and land (right panels). (a) and (b): Zonal mean
1TS increases monotonically with increase in the magnitude of
maximum concentration of aerosols over poles and decreases with
increase in the magnitude of tropical maximum. (c) and (d): polar
maximum causes enhanced precipitation. (e) and (f): polar maximum causes enhanced precipitation minus evaporation. Results
shown are averages of the last 30 years of 60-year simulations.
Figure 5. Zonal means of change in surface temperature (1TS),
precipitation (1P) and precipitation minus evaporation (1PmE).
(a) Zonal mean 1TS increases monotonically with increase in maximum concentrations over the poles and decreases with increase
in tropical maxima. (b) Zonal mean 1P: polar maximum causes
enhanced precipitation. (c) Zonal mean 1PmE; polar maximum
causes enhanced precipitation minus evaporation. Results shown
are averages of the last 30 years of 60-year simulations.
the precipitation response around the equator is exactly opposite to the response in 2 × CO2 case. This could be due to the
overcooling of the tropics in the Tropics scenarios. However,
the robust feature in the zonal-mean precipitation changes
between the geoengineering cases and the control case is a
monotonic increase at all latitudes when polar weighting is
increased. This monotonicity is similar to the monotonicity
seen in the global mean values. The changes in zonal mean
precipitation minus evaporation (water budget) are similar to
changes in zonal mean precipitation (Fig. 5c, 6e and f).
Figure 8 shows the spatial pattern of the radiative forcing in selected simulations: 2 × CO2 , Uniform, Polar3, Tropics1, Polar6 and Tropics3 cases. We notice that the radiative forcing in the 2 × CO2 case is significant over the whole
globe but not significant in most regions in the geoengineering cases. The radiative forcing is positive in most locations
in Polar cases. In the Tropics cases, the forcing is negative in
the tropical regions and positive in the polar regions.
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Figure 7. Zonal mean precipitation over the globe. The position
of intertropical convergence zone (ITCZ) remains the same in all
the geoengineering cases. The zonal mean precipitation decreases
monotonically over the equator as the global mean radiative forcing
increases. Results shown are averages of the last 30 years of 60-year
simulations.
In the 2 × CO2 case, both temperature and precipitation changes are large and significant over the whole globe
(Fig. 9). The temperature increase over poles is much larger
than in the tropics, in agreement with previous studies
(Caldeira and Wood, 2008; Lunt et al., 2008; Matthews and
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A. Modak and G. Bala: Sensitivity of climate to latitudinal distribution of solar reduction
Figure 8. Spatial pattern of radiative forcing in the 2 × CO2 , Uniform, and some polar and tropic geoengineering scenarios. In the
Uniform and Tropics cases, there is a residual positive forcing in
the high latitudes and negative forcing in the low latitudes indicating an inexact compensation. Hatching indicates the region where
the changes are significant at 1 % level. Significance level was estimated by Student’s t test. Results shown are averages of the last
20 years of 30-year simulations with fixed sea surface temperature
and sea ice fraction.
Caldeira, 2007; Robock et al., 2008; Rasch et al., 2008b). The
uniform geoengineering case (Uniform) shows mitigation in
temperature with reduced precipitation relative to 1 × CO2 .
This is because of different fast precipitation response to
CO2 forcing and solar forcing. In Polar3 case, the change
in precipitation is largely offset but there is significant warming over large regions. However, temperature is largely offset in Tropics1 but there is decrease in precipitation relative to the uniform distribution case. The last four panels of
Fig. 9 shows the extreme cases; the case with largest polar
weighting (Polar6) significantly warms the planet while the
case with largest tropical weighting (Tropics3) overcools the
planet with large reduction in precipitation.
Atmos. Chem. Phys., 14, 7769–7779, 2014
Figure 9. Changes in annual-mean surface temperature (left panels) and precipitation (right panels) in the 2 × CO2 , Uniform, and
some Polar and Tropics geoengineering scenarios relative to the
control (1 × CO2 ). Hatching indicates the region where the changes
are significant at 1 % level. Significance level was estimated using
Student’s t test. Both surface temperature and precipitation changes
are large and significant everywhere in the 2 × CO2 and extreme
scenarios (Polar6 and Tropics3). Although significant over large regions, both temperature and precipitation changes are small in the
Uniform case. Polar3 scenario offsets global mean precipitation but
not global mean temperature while Tropics1 scenario offsets global
mean temperature but with reduced precipitation. Results shown are
averages of the last 30 years of 60-year simulations.
4
Discussion and conclusions
In this study, for a fixed total amount of sulfate aerosols
which when distributed uniformly nearly offsets the global
mean temperature change from a doubling of CO2 , there is
a residual cooling when the aerosol concentration is maximized near the tropical regions and warming when concentration is maximized near the polar regions (Fig. 1c).
Consequent changes in global mean precipitation are simulated as dictated by the hydrological sensitivity of the model
(Fig. 1b). We also observe a similar monotonic increase in
the precipitation intensity as the maximum aerosol concentration over the poles increases (Figs. 10, 11 and 12). The
increases are of the order of 10 % for low intensity (5th
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A. Modak and G. Bala: Sensitivity of climate to latitudinal distribution of solar reduction
Figure 10. Percentile values (p5, p25, median, p75, p85, p90, p95
and p99) of precipitation intensity over Globe. There is a monotonic
increase in precipitation for all percentile values as the maximum
concentration of aerosols over poles increases. Grid-level monthly
mean precipitation are used to calculate the percentile values. The
last 30 years of 60-year simulations are used for the statistics.
Figure 11. Percentile values (p5, p25, median, p75, p85, p90, p95
and p99) of precipitation intensity over Land. There is a monotonic
increase in precipitation for all percentile values as the maximum
concentration of aerosols over poles increases. Grid-level monthly
mean precipitation over all land points are used to calculate the percentile values.The last 30 years of 60-year simulations are used for
the statistics.
percentile) and 2–3 % for large intensity (99th percentile) between the extreme cases (Tropics3 and Polar6).
Our result that the global mean precipitation is reduced
when aerosol concentration is maximized at the equator is
in agreement with a recent study that shows a drastic reduction in tropical rainfall when aerosol concentration is maximum in the tropics (Ferraro et al. 2014). However, there are
quantitative differences because the prescription of aerosols
is different in the two studies. In Ferraro et al. (2014), the sulfate aerosols are prescribed approximately at 50 hPa (lower
stratosphere) while we prescribe them at TOM. Further, compared to our aerosol size (dry median radius ≈ 0.05 µm) the
aerosol size used in Ferraro et al. (2014) is larger (dry median
radius ≈ 0.1 µm).
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7777
Figure 12. Percentile values (p5, p25, median, p75, p85, p90, p95
and p99) of precipitation intensity over Ocean. There is a monotonic
increase in precipitation for all percentile values as the maximum
concentration of aerosols over poles increases. Grid-level monthly
mean precipitation over all ocean points are used to calculate the
percentile values.The last 30 years of 60-year simulations are used
for the statistics.
In agreement with earlier studies (e.g., Bala et al., 2008),
we find that both temperature and precipitation changes cannot be offset simultaneously. In agreement with this, not only
in a simulation with uniform distribution but in all the geoengineering simulation with different latitudinal distribution
(that is, even with non-uniform distribution of solar insolation reduction), we find that it is not possible to offset both
temperature and precipitation changes simultaneously. The
latitudinal distribution which offsets the warming leads to a
drier climate while the distribution which offsets the precipitation results in a relatively warmer world (note that Bala et
al. (2008) used a uniform solar insolation reduction). For a
fixed total amount of aerosols but with different latitudinal
distribution it is possible to achieve a range of global mean
radiative forcing and thus a range of climate states.
Our findings should be viewed in the light of the limitations and uncertainties involved in this study. Our simulations are highly idealized as we have prescribed sulfate
aerosol (to reduce the solar insolation) instead of injecting
and transporting them. We have prescribed a fixed particle
size distribution but particle size distribution would evolve
with time and is shown to be important in precisely estimating the effects on different climate variables (Rasch et
al., 2008b). Some modeling studies (Robock et al., 2008)
have injected aerosol precursors into the stratosphere with
fixed particle size distribution while other studies (Heckendorn et al., 2009; Pierce et al., 2010; Niemeier et al., 2010;
Hommel and Graf, 2011; English et al., 2012) have demonstrated the importance of including the microphysics of particle growth. Further, we have focused our investigation primarily on global mean climate while several other studies
(e.g., Robock et al., 2008; Irvine et al., 2010; Ricke et al.,
2010) focused on regional disparities.
Atmos. Chem. Phys., 14, 7769–7779, 2014
7778
A. Modak and G. Bala: Sensitivity of climate to latitudinal distribution of solar reduction
In this study, we have not considered the consequences of
detailed stratospheric dynamics and sulfate aerosol chemistry
on the ozone layer (Tilmes et al., 2009). Thus our model does
not account for the ozone loss that might take place due to
the increased stratospheric sulfate aerosols. Our model lacks
a dynamic ocean and sea ice components, and thus the effects of deep ocean circulation are not modeled here. Further, in this model an interactive land carbon cycle is not included and hence the impact of changes in the diffuse fraction of surface solar radiation due to stratospheric aerosols
could not be investigated. We intend to use a later version of
the model that includes carbon cycle to investigate the impacts of altered diffuse radiation in a future study. However,
we believe our results on temperature and precipitation is so
fundamental that they would be unchanged when additional
components and feedbacks are included.
In summary, for a fixed total mass of aerosols, we find that
the global mean climate is warmer and wetter when aerosol
concentration is maximum over the poles relative to the uniform distribution case (which offsets global mean temperature change) because the global mean residual radiative forcing is positive in these cases when compared to the Uniform
case. The opposite is true when aerosol concentration is maximum in the tropics. Further, our study clearly indicates that
knowledge of the global mean radiative forcing, not the details of latitudinal distribution of aerosols, is sufficient to infer the global mean climate change.
Acknowledgements. Financial support for A. Modak was provided
by the Divecha Centre for Climate Change, Indian Institute of
Science. We thank the Supercomputer Education and Research
Centre, Indian Institute of Science for providing the computational
resources.
Edited by: M. K. Dubey
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